Papers Modality completion
“Modality completion” 태그가 달린 논문 10편 · 필터 해제
GSDNet: Revisiting Incomplete Multimodal-Diffusion from Graph Spectrum Perspective for Conversation Emotion Recognition
Multimodal emotion recognition in conversations (MERC) aims to infer the speaker's emotional state by analyzing utterance information from multiple sources (i.e., video, audio, and text). Compared with unimodality, a mor…
Emotion RecognitionModality completionMultimodal Emotion RecognitionUniMoCo: Unified Modality Completion for Robust Multi-Modal Embeddings
Current research has explored vision-language models for multi-modal embedding tasks, such as information retrieval, visual grounding, and classification. However, real-world scenarios often involve diverse modality comb…
Image to textInformation RetrievalModality completionVisual GroundingRGL: A Graph-Centric, Modular Framework for Efficient Retrieval-Augmented Generation on Graphs
Recent advances in graph learning have paved the way for innovative retrieval-augmented generation (RAG) systems that leverage the inherent relational structures in graph data. However, many existing approaches suffer fr…
Abstract generationGraph LearningModality completion+3Knowledge Bridger: Towards Training-free Missing Modality Completion
Previous successful approaches to missing modality completion rely on carefully designed fusion techniques and extensive pre-training on complete data, which can limit their generalizability in out-of-domain (OOD) scenar…
Knowledge GraphsModality completionAMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation
In clinical practice, full imaging is not always feasible, often due to complex acquisition protocols, stringent privacy regulations, or specific clinical needs. However, missing MR modalities pose significant challenges…
Brain Tumor SegmentationImputationModality completionTumor SegmentationLeveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Federated learning (FL) has obtained tremendous progress in providing collaborative training solutions for distributed data silos with privacy guarantees. However, few existing works explore a more realistic scenario whe…
Federated LearningImage-text ClassificationModality completiontext-classification+2MC-DBN: A Deep Belief Network-Based Model for Modality Completion
Recent advancements in multi-modal artificial intelligence (AI) have revolutionized the fields of stock market forecasting and heart rate monitoring. Utilizing diverse data sources can substantially improve prediction ac…
Missing ValuesModality completionModality Bank: Learn multi-modality images across data centers without sharing medical data
Multi-modality images have been widely used and provide comprehensive information for medical image analysis. However, acquiring all modalities among all institutes is costly and often impossible in clinical settings. To…
AllMedical Image AnalysisModality completionModality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation
In large studies involving multi protocol Magnetic Resonance Imaging (MRI), it can occur to miss one or more sub-modalities for a given patient owing to poor quality (e.g. imaging artifacts), failed acquisitions, or hall…
Brain Tumor SegmentationModality completionSegmentationTumor SegmentationHetero-Modal Variational Encoder-Decoder for Joint Modality Completion and Segmentation
We propose a new deep learning method for tumour segmentation when dealing with missing imaging modalities. Instead of producing one network for each possible subset of observed modalities or using arithmetic operations …
DecoderModality completionSegmentation